• Journal of the Institute of Convergence Signal Processing
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• v.9 no.3
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• pp.195-200
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• 2008

To compress the moving picture data effectively, it is needed to reduce spatial and temporal redundancy of input image data. While motion estimation! compensation methods is effectively able to reduce temporal redundancy but it is increased computation complexity because of the prediction between frames. So, the study of algorithm for computation reduction and real time processing is needed. This paper is presenting quantizer effectively able to quantize DCT coefficient considering the human visual sensitivity. As quantizer that proposed DCT-based H.263 could make transmit more frame than TMN5 at a same transfer speed, and it could decrease the frame drop effect. And the luminance signal appeared the difference of $-0.3{\sim}+0.65dB$ in the average PSNR for the estimation of objective image quality and the chrominance signal appeared the improvement in about 1.73dB in comparision with TMN5. The proposed method reduces $30{\sim}31%$ compared with NTSS and $20{\sim}21%$ compared to 4SS in comparition of calculation quantity.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.347-358
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• 2009

In this thesis, we develop a vision based hand motion recognition system using a camera with two rotational motors. Existing systems were implemented using a range camera or multiple cameras and have a limited working area. In contrast, we use an uncalibrated camera and get more wide working area by pan-tilt motion. Given an image sequence provided by the pan-tilt camera, color and pattern information are integrated into a tracking system in order to find the 2D position and direction of the hand. With these pose information, we estimate 3D motion plane on which the gesture motion trajectory from approximately forms. The 3D trajectory of the moving finger tip is projected into the motion plane, so that the resolving power of the linear gesture patterns is enhanced. We have tested the proposed approach in terms of the accuracy of trace angle and the dimension of the working volume.

• Journal of Digital Contents Society
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• v.13 no.2
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• pp.255-262
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• 2012

Human motion tracking algorithm is receiving attention from many research areas, such as human computer interaction, video conference, surveillance analysis, and game or entertainment applications. Over the last decade, various tracking technologies for each application have been demonstrated and refined among them such of real time computer vision and image processing, advanced man-machine interface, and so on. In this paper, we introduce cost-effective and real-time human motion tracking algorithms based on depth image 3D point matching with a given superellipsoid body representation. The body representative model is made by using parametric volume modeling method based on superellipsoid and consists of 18 articulated joints. For more accurate estimation, we exploit initial inverse kinematic solution with classified body parts' information, and then, the initial pose is modified to more accurate pose by using 3D point matching algorithm.

• Smart Media Journal
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• v.12 no.11
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• pp.48-56
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• 2023

The technology of Three-dimensional human posture estimation is used in sports, motion recognition, and special effects of video media. Among various methods for this, multi-view 3D human pose estimation is essential for precise estimation even in complex real-world environments. But Existing models for multi-view 3D human posture estimation have the disadvantage of high order of time complexity as they use 3D feature maps. This paper proposes a method to extend an existing monocular viewpoint multi-frame model based on Transformer with lower time complexity to 3D human posture estimation for multi-viewpoints. To expand to multi-viewpoints our proposed method first generates an 8-dimensional joint coordinate that connects 2-dimensional joint coordinates for 17 joints at 4-vieiwpoints acquired using the 2-dimensional human posture detector, CPN(Cascaded Pyramid Network). This paper then converts them into 17×32 data with patch embedding, and enters the data into a transformer model, finally. Consequently, the MLP(Multi-Layer Perceptron) block that outputs the 3D-human posture simultaneously updates the 3D human posture estimation for 4-viewpoints at every iteration. Compared to Zheng[5]'s method the number of model parameters of the proposed method was 48.9%, MPJPE(Mean Per Joint Position Error) was reduced by 20.6 mm (43.8%) and the average learning time per epoch was more than 20 times faster.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.145-155
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• 2013

In this paper, we proposed a $4{\times}4$ block parallel architecture of interpolation for high-performance H.264/AVC Fractional Motion Estimation in 8K UHD($7680{\times}4320$) video real time processing. To improve throughput, we design $4{\times}4$ block parallel interpolation. For supplying the $10{\times}10$ reference data for interpolation, we design 2D cache buffer which consists of the $10{\times}10$ memory arrays. We minimize redundant storage of the reference pixel by applying the Search Area Stripe Reuse scheme(SASR), and implement high-speed plane interpolator with 3-stage pipeline(Horizontal Vertical 1/2 interpolation, Diagonal 1/2 interpolation, 1/4 interpolation). The proposed architecture was simulated in 0.13um standard cell library. The gate count is 436.5Kgates. The proposed H.264/AVC Fractional Motion Estimation can support 8K UHD at 30 frames per second by running at 187MHz.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.3
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• pp.23-35
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• 2002

Gaze detection is to locate the position on a monitor screen where a user is looking. In our work, we implement it with a computer vision system setting a single camera above a monitor and a user moves (rotates and/or translates) his face to gaze at a different position on the monitor. To detect the gaze position, we locate facial region and facial features(both eyes, nostrils and lip corners) automatically in 2D camera images. From the movement of feature points detected in starting images, we can compute the initial 3D positions of those features by camera calibration and parameter estimation algorithm. Then, when a user moves(rotates and/or translates) his face in order to gaze at one position on a monitor, the moved 3D positions of those features can be computed from 3D rotation and translation estimation and affine transform. Finally, the gaze position on a monitor is computed from the normal vector of the plane determined by those moved 3D positions of features. As experimental results, we can obtain the gaze position on a monitor(19inches) and the gaze position accuracy between the computed positions and the real ones is about 2.01 inches of RMS error.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.10
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• pp.825-834
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• 2000

광학식 동작 포착(optical motion capture)시스템에서 신뢰할만한 3차원 좌표의 획득과 마커의 궤적 추적은 매우 중요한 문제이다. 3차원 좌표를 획득하기 이해서는 다중의 카메라로부터 2차원의 데이터 간의 대응관계를 구해야 한다. 본 논문에서는 각 카메라에서의 3차원 마커들 간의 대응관계를 k-partite graph로 모델링하고, 릴렉세이션 알고리즘을 사용하여 고스트가 제거된 신뢰성있는 클릭을 추출한다. 이를 통해 정확하고 안정적인 3차원의 좌표를 생성할 수 있다. 또한 추출된 3차원 마커의 궤적의 추적을 위해 칼만 필터를 사용한 마커의 예측과 데이터 연계 문제의 해결을 위한 전략을 제안하고. 사라진 마커의 궤적을 유지시키기 위해 다이나믹 모델을 사용한 추적 알고리즘을 제시한다.

• Journal of Broadcast Engineering
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• v.17 no.4
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• pp.611-624
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• 2012

'Gesture' is the most intuitive means of communication except the voice. Therefore, there are many researches for method that controls computer using gesture input to replace the keyboard or mouse. In these researches, the method of user detection and main body parts estimation is one of the very important process. in this paper, we propose user objects detection and main body parts estimation method on inaccurate depth information for pose estimation. we present user detection method using 2D and 3D depth information, so this method robust to changes in lighting and noise and 2D signal processing 1D signals, so mainly suitable for real-time and using the previous object information, so more accurate and robust. Also, we present main body parts estimation method using 2D contour information, 3D depth information, and tracking. The result of an experiment, proposed user detection method is more robust than only using 2D information method and exactly detect object on inaccurate depth information. Also, proposed main body parts estimation method overcome the disadvantage that can't detect main body parts in occlusion area only using 2D contour information and sensitive to changes in illumination or environment using color information.

• Journal of Broadcast Engineering
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• v.9 no.3
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• pp.196-206
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• 2004

This paper presents an efficient joint disparity-motion estimation algorithm for stereo sequence CODEC. Disparity vectors are estimated by the left and right motion vectors and previous disparity vectors for every frame. In order to obtain more accurate disparity vectors. we include a spatial prediction Process after the feint estimation. From joint estimation and spatial prediction, we can obtain accurate disparity vectors and then Increase coding efficiency. Finally, we proposed the backward quadtree decomposition. which helps the encoder to have a more detailed disparity vector map without transmitting additional coding bits for quadtree information. We confirmed superior performance of the proposed method through computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2112-2122
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• 1997

This paper presents a new video codec which is based on 2-D triangular mesh-based motion compensation and two step grid point motion estimation. With this approach the efficiency of compression and the quality of reconstructed images are improved. The compensation of motion for each triangular patch is performed by image warping using motion vectors at the grid points. The prediction error coding and the rate control meet MPEG-4 VM 3.0 specification. The experimental results show that the codec system proposed is simple in complexity and moreover, the quality of decoded images is improved.